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Security audit

Auto Researcher

Security checks for vulnerabilities and agentic risk

Overview

This research skill is not malicious, but it asks agents to use monitoring, memory storage, scheduling, and shell-style execution without enough user controls or scope limits.

Install only if you are comfortable with a research assistant that may search the web, store research data, and create recurring monitoring jobs. Before using it, set explicit limits for research scope, monitoring duration, storage location, deletion, and require confirmation before any exec command or scheduled task is used.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Findings (6)

Intent-Code Divergence

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The file declares runtime: prompt_only, but later describes operation via external tools such as exec, web_fetch, memory/store, scheduling, and search. This mismatch can mislead reviewers and deployment systems about the skill's capabilities, causing it to be approved or invoked under weaker assumptions than its documented behavior warrants.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
88% confidence
Finding

The skill advertises continuous monitoring and update notifications, but does not warn users that this implies persistent observation, repeated external access, and possible outbound alerts. That creates consent and privacy risks, especially if users do not realize the behavior continues beyond the initial request.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The knowledge-graph and raw-data storage features describe retaining collected entities, relations, and appendices without any retention, minimization, or sensitivity guidance. Research tasks can easily collect personal, proprietary, or copyrighted material, so undocumented storage increases privacy and compliance risk.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The activation phrases are broad, natural-language requests such as '帮我研究一下...' and '持续监控...'. Without scope limits, confirmation gates, or task-boundary rules, the skill may trigger on ordinary conversation and start wide research, monitoring, or data-collection behaviors the user did not intend to authorize.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The skill is presented as a research assistant, but the documented OpenClaw adaptation maps functionality to an exec tool without constraining what commands may run or why shell execution is required. Even in documentation, introducing generic command execution expands the implied privilege boundary and can lead downstream agents or integrators to invoke local commands for untrusted research tasks, increasing command-injection and unintended system-action risk.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
90% confidence
Finding

The description, instructions, and activation examples are entirely in Chinese, which effectively forces a single language experience. There is no statement that the skill is China-specific or any option for the user to choose another language.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.